Fascinated by chemistry since my childhood I began my undergraduate studies at the University of Bayreuth, Germany in 1992 where I obtained my BSc. in 1998. Following my enthusiasm for inorganic syntheses and the beauty of the structures of extended solids I devoted my PhD studies to the synthesis and crystal structure determination of phosphorus(V)-nitrides with Wolfgang Schnick at University of Munich (LMU), Germany. This ceramic class of compounds was challenging to access systematically at the time. We developed a novel synthetic pathway that allowed for its systematic access and discovered a number of interesting solid state structures. I completed my PhD work in 2001.


I became attracted to the new and very rapidly evolving field of nanostructured materials and joined Geoffrey A. Ozin as a postdoctoral fellow at the University of Toronto. I worked on Periodic Mesoporous Organosilicas (PMOs) that are nanoscopically ordered ¡°soft matter¡± that ¡°self-assemble¡± under ambient aqueous conditions and allow for the synergistic integration of inorganic and organic building units in mesoscopically ordered frameworks. We were able to considerably expand the scope of building blocks for PMOs and also found a range of intriguing materials properties that suggest applications as low dielectric constant materials in microelectronics.   


In 2005 I accepted an offer from Lehigh University where I am currently working as an assistant professor of chemistry. Our goal is to achieve control in synthesis and structure of inorganic and organic-inorganic hybrid solid state materials over multiple length scales. We aim to achieve complexity in extended solid state structures that contain multiple organic and inorganic components by design. This is a very ambitious goal because of the incredibly complex interactions in multi-component chemical systems making it extremely difficult to direct syntheses and structures. To reach this goal we focus on the utilization of all available chemical bonding forces in creative combinations that minimize synthetic effort while maximize predictability.